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DTSTART;TZID=America/Los_Angeles:20260529T110000
DTEND;TZID=America/Los_Angeles:20260529T123000
DTSTAMP:20260515T164420Z
CREATED:20260515T164420Z
LAST-MODIFIED:20260515T164420Z
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SUMMARY:Zhou\, K. (CSE) - Toward Safer Frontier AI: From Evaluation and Red-Teaming to Alignment and Oversight
DESCRIPTION:This dissertation investigates how to make modern AI systems safer as they grow more capable. It addresses two central sources of risk: malicious misuse\, in which adversarial users coerce models into harmful behavior\, and internal misalignment\, in which models themselves pursue goals that diverge from human intent through deception\, sandbagging\, or other covert behaviors. The dissertation identifies novel safety risks in frontier multimodal large language models and AI agents\, introduces a black-box red-teaming framework for AI agents\, proposes new safety alignment algorithms\, and builds the first probe-based misalignment monitoring system\, developing practical approaches for evaluating\, red-teaming\, aligning\, and overseeing frontier language models and agents. The central conclusion is that responsible AI cannot rest on any single guardrail: capability-scaled evaluation\, active red-teaming\, training-time alignment\, and scalable monitoring together form a coordinated stack for frontier AI safety. \nEvent Host: Kaiwen Zhou\, Ph.D. Candidate\, Computer Science & Engineering  \nAdvisor: Xin Wang \nZoom: https://ucsc.zoom.us/j/94196702062?pwd=b9LJMfL232ixG2THMab8XuJ32a4FVD.1 \nPasscode:  584794
URL:https://events.ucsc.edu/event/zhou-k-cse-toward-safer-frontier-ai-from-evaluation-and-red-teaming-to-alignment-and-oversight/
CATEGORIES:Ph.D. Presentations
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DTSTART;TZID=America/Los_Angeles:20260528T130000
DTEND;TZID=America/Los_Angeles:20260528T150000
DTSTAMP:20260514T160625Z
CREATED:20260514T160341Z
LAST-MODIFIED:20260514T160625Z
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SUMMARY:Yang\, D. (CSE) - Inner Monologue: a Pathway to Human-Like Reasoning for Complex Tasks
DESCRIPTION:A central goal on the path toward general AI is to build systems capable of deliberative reasoning before action. Such systems should inspect what they know\, identify what they need\, seek or construct useful information\, and revise their reasoning through intermediate cognitive states. This dissertation studies this goal through the lens of Inner Monologue (IM)\, a mechanism that enables AI systems to coordinate internal components\, acquire external information\, and reason through structured intermediate states. \nI will first introduce IM as a mechanism for internal coordination in static information systems\, where multiple models collaborate within one AI system to solve reasoning tasks. I will then extend IM to dynamic information systems\, where AI system is learned to retrieve external information. Finally\, I will present how IM can move beyond verbal reasoning toward multimodal thinking\, where generated visual states represent the system’s current understanding and support iterative refinement. \nTogether\, this dissertation demonstrates the success and potential of human-inspired Inner Monologue mechanisms for improving complex multi-step reasoning in AI systems. \nEvent Host: Diji Yang\, Ph.D. Candidate\, Computer Science & Engineering \nAdvisor: Yi Zhang \nZoom: https://ucsc.zoom.us/j/99915235963?pwd=7Jqo6fc83LWobTEYRZCUzbrWbeov3Y.1 \nPasscode: 7Jqo6fc83LWobTEYRZCUzbrWbeov3Y.1
URL:https://events.ucsc.edu/event/yang-d-cse-inner-monologue-a-pathway-to-human-like-reasoning-for-complex-tasks/
LOCATION:Silicon Valley Campus\, 3175 Bowers Avenue\, Santa Clara\, CA\, 95054\, United States
CATEGORIES:Ph.D. Presentations
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260528T120000
DTEND;TZID=America/Los_Angeles:20260528T140000
DTSTAMP:20260526T163353Z
CREATED:20260526T163353Z
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SUMMARY:Ortiz Barbosa\, D. (CSE) - HARDENING AUTONOMOUS CYBER-PHYSICAL SYSTEMS AGAINST ADVERSARIAL CONDITIONS
DESCRIPTION:Autonomous systems\, such as Autonomous Vehicles (AVs) and drones\, are increasingly\ndeployed across a wider array of contexts for both civilian and military use. As these\nsystems become more common\, they may be targeted by malicious actors seeking to\nexploit and abuse them\, compromising safety-critical operations. Among the ways to\nprotect these systems simulation based testing frameworks have been developed. How-\never\, existing testing frameworks primarily focus on identifying logical flaws or system\nvulnerabilities\, often emphasizing static scenarios and paying less attention to an adap-\ntive intelligent adversary.\nTo help reduce this gap\, this dissertation develops and applies adaptive\, adversary-\naware methodologies to discover\, formalize\, and mitigate security vulnerabilities in au-\ntonomous systems spanning vehicle platooning\, drone swarms\, and vision-based drone\nrecovery. We first apply NLP techniques to discover and formalize driving rules across\nNorth American and Australian jurisdictions\, identifying possible restriction that an\nadversary can exploit. Likewise\, these rules can be used to test the adaptability of AVs\nto new contexts and to establish a formal basis for context-aware AV testing. Next\,\nwe apply optimization-based adversarial search to both ACC-controlled vehicle pla-\ntoons and obstacle-avoiding drone swarms. We uncover maneuvers that an adversary\ncan use against the system that range from crash-inducing patterns against platooning\ncontrollers to herding strategies that divert swarms from their objectives. Finally\, to\naddress the gap regarding the possible solutions to an adversarial attack we explore how\na drone can recover from it by using LVLMs to understand its context and select a safe\nlanding surface. \nEvent Host: Diego Ortiz Barbosa\, Ph.D. Candidate\, Computer Science & Engineering  \nAdvisor: Alvaro A Cardenas
URL:https://events.ucsc.edu/event/ortiz-barbosa-d-cse-hardening-autonomous-cyber-physical-systems-against-adversarial-conditions/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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DTSTART;TZID=America/Los_Angeles:20260528T110000
DTEND;TZID=America/Los_Angeles:20260528T120000
DTSTAMP:20260522T165248Z
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SUMMARY:Oh\, S. (CSE) - Efficient Instruction Supply for Datacenter Processors
DESCRIPTION:Modern datacenter CPUs lose 25–66% of execution cycles to instruction-delivery stalls. This bottleneck persists\, despite the recent trend towards accelerators and GPUs\, as there is continuing demand by applications that only execute on CPUs. Two workload classes dominate today’s datacenter execution cycles: hyperscale server software (databases\, build systems\, and content stores)\, whose large instruction footprints create severe frontend pathologies; and agentic AI systems\, in which large-language-model agents plan\, dispatch tools\, and maintain growing conversational contexts\, causing CPUs to account for up to 88% of end-to-end agent latency. Reflecting this shift\, major CPU vendors have publicly repositioned the CPU as the orchestration layer of the AI stack and have begun shipping processors optimized for agent-centric workloads. \nThis dissertation argues that instruction delivery is the dominant CPU bottleneck across both workload classes and that the recent trend towards agentic AI further exacerbates this challenge. In hyperscale server binaries\, the primary pathologies are wrong-path prefetch pollution and post-recovery instruction-delivery gaps across large\, irregular call graphs. In agentic AI systems\, the bottleneck shifts to an orchestration substrate composed of protocol stacks\, dynamic-runtime dispatch\, and agent-specific extensions that is even more frontend-bound than traditional warehouse-scale workloads. \nTo address these bottlenecks\, this dissertation presents three technical contributions\, together with a companion infrastructure contribution. First\, Utility-Driven Prefetching (UDP) extends fetch-directed instruction prefetching (FDIP) with a learned per-prefetch utility model that admits candidates based on their historical contribution to demand-fetch hits\, including those reached along wrong-path execution. Second\, Junction-based Unified Miss-point Prefetching (JUMP) addresses the post-recovery instruction-delivery gap that UDP and prior FDIP optimizations cannot reach by launching a lightweight secondary FDIP thread at a learned miss point following each branch-prediction failure. Across a suite of datacenter workloads\, UDP improves IPC by 3.6% on average (up to 16.1%) over a state-of-the-art FDIP baseline\, while JUMP improves IPC by 2.0% on average (up to 14.9%). Combined\, the two mechanisms substantially close the gap between FDIP and a perfect L1 instruction cache at a storage cost of only a few tens of kilobytes.\nThird\, this dissertation introduces the Agentic Tax\, the first CPU characterization study of agentic AI workloads across three runtime families. The study is packaged as a deterministic-replay benchmark infrastructure that enables repeatable\, cycle-level evaluation under controlled conditions. The characterization shows that the orchestration substrate of agentic AI workloads is significantly more frontend-bound than the hyperscale datacenter workloads examined in prior work\, and that it introduces new dominant function families with no analog in traditional warehouse-scale systems. These findings motivate two architectural directions proposed as future work: extending UDP and JUMP to optimize the orchestration substrate itself\, and designing heterogeneous CPU cores that allocate frontend resources according to the execution phase. \nEvent Host: Surim Oh\, Ph.D. Candidate\, Computer Science & Engineering  \nAdvisor: Heiner Litz \nZoom: https://ucsc.zoom.us/j/94753352649?pwd=7vQxlnSJkUb0KfG3t6STo639LhRv7j.1 \nPasscode: 205162
URL:https://events.ucsc.edu/event/oh-s-cse-efficient-instruction-supply-for-datacenter-processors/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260527T120000
DTEND;TZID=America/Los_Angeles:20260527T140000
DTSTAMP:20260518T162624Z
CREATED:20260518T162624Z
LAST-MODIFIED:20260518T162624Z
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SUMMARY:Zheng\, Y. (CSE) - Extending eBPF Beyond Kernel Extensions: Verified Interfaces for Runtime System Extensibility
DESCRIPTION:Modern system software increasingly needs runtime extensibility: userspace applications need safe ways to expose domain-specific extension points\, GPU resource management needs workload-specific memory and scheduling policies\, and kernel eBPF JIT compilers need different runtime optimizations as workloads and hardware vary. However\, built-in policies are safe but difficult to specialize across rapidly changing workloads and hardware environments\, limiting efficiency\, while code modifications are flexible but difficult to deploy safely. This dissertation argues that verified eBPF interfaces can turn eBPF from a kernel-extension mechanism into a general substrate for safe runtime extensibility. In this model\, trusted mechanisms expose narrow\, constrained programmable hooks; extensions declare their requirements; verifier-enforced checks preserve safety; and execution remains low-overhead. \nI develop this thesis through three systems spanning userspace applications\, heterogeneous GPU subsystems\, and the kernel eBPF compiler itself. EIM\, implemented in bpftime\, applies verified eBPF interfaces to userspace applications\, allowing application behavior to be extended through explicit constraints and efficient userspace eBPF execution. gpu_ext extends the same idea to heterogeneous systems by exposing programmable resource management hooks for GPU memory and scheduling policy across driver and device. BpfReJIT with kinsn makes the eBPF JIT compiler itself extensible: it enables runtime-guided optimization through dynamic recompilation and extends eBPF bytecode to express diverse hardware capabilities. Together\, these systems show how verified eBPF interfaces can support safe programmability\, separation of policy and mechanisms\, and runtime specialization across applications\, GPU subsystems\, and the kernel JIT infrastructure. \nEvent Host: Yusheng Zheng\, Ph.D. Student\, Computer Science & Engineering \nAdvisor: Andi Quinn \nZoom: 504 350 0245 \nPasscode: 521336
URL:https://events.ucsc.edu/event/zheng-y-cse-extending-ebpf-beyond-kernel-extensions-verified-interfaces-for-runtime-system-extensibility/
CATEGORIES:Ph.D. Presentations
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DTSTART;TZID=America/Los_Angeles:20260527T110000
DTEND;TZID=America/Los_Angeles:20260527T123000
DTSTAMP:20260330T203942Z
CREATED:20260330T203942Z
LAST-MODIFIED:20260330T203942Z
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SUMMARY:CSE Colloquium - Learning to Image: Computational Microscopy for Dynamic Systems
DESCRIPTION:Presenter: Laura Waller\, UC Berkeley \nAbstract: \nComputational imaging jointly designs hardware and algorithms to push beyond the classical limits of imaging\, enabling measurement of new quantities (e.g. 3D\, phase\, and super-resolution) with simple\, inexpensive hardware. These approaches have already transformed consumer photography; our goal is to achieve a similar transformation in scientific microscopy. \nIn this talk\, I will show how end-to-end learning is reshaping the design of imaging systems\, from programmable illumination with LED arrays to compact\, lensless cameras built from Scotch tape. By combining physical models with neural networks\, we can jointly learn how to capture data\, reconstruct images\, and self-calibrate systems that would otherwise be too complex to model. However\, many computational methods rely on multiple measurements\, limiting their use for live\, dynamic samples. I will introduce new space-time algorithms based on implicit neural representations (INRs) that jointly recover structure and motion\, correct artifacts\, and enable high-resolution imaging in regimes where traditional approaches fail. \nBio: \nLaura Waller is the Charles A. Desoer Professor of Electrical Engineering and Computer Sciences at UC Berkeley. She received B.S.\, M.Eng. and Ph.D. degrees from the Massachusetts Institute of Technology in 2004\, 2005 and 2010. After that\, she was a Postdoctoral Researcher and Lecturer of Physics at Princeton University from 2010-2012. She is a Packard Fellow for Science & Engineering\, Moore Foundation Data-driven Investigator\, OSA Fellow\, and Chan-Zuckerberg Biohub Investigator. She has received the Carol D. Soc Distinguished Graduate Mentoring Award\, OSA Adolph Lomb Medal\, the SPIE Early Career Award and the Max Planck-Humboldt Medal. \nHosted by: Professor Alvaro Cardenas \nLocation: Engineering 2\, Room E2-180 (Refreshments such as fruit\, pastries\, coffee\, and tea will be provided.) \nZoom Option: https://ucsc.zoom.us/j/93445911992?pwd=YkJ2TQtF79h0PcNXbEcpZLbpK0coiY.1&jst=3
URL:https://events.ucsc.edu/event/cse-colloquium-learning-to-image-computational-microscopy-for-dynamic-systems/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260527T090000
DTEND;TZID=America/Los_Angeles:20260527T110000
DTSTAMP:20260518T163634Z
CREATED:20260518T163634Z
LAST-MODIFIED:20260518T163634Z
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SUMMARY:Tu\, H. (CSE) - From Evaluation to Adaptation: Building Reliable Multimodal Intelligence
DESCRIPTION:Multimodal large language models (MLLMs) are rapidly becoming general-purpose AI systems\, yet their capabilities are advancing faster than our ability to evaluate\, improve\, and validate their reliability in realistic use. Standard benchmarks mainly measure in-distribution final-answer accuracy\, leaving critical gaps in safety\, robustness\, fine-grained reasoning evaluation\, and reliability in real-world agentic settings. My research proposes an evaluation-to-adaptation framework for building reliable multimodal intelligence: developing rigorous evaluations that expose failures beyond conventional benchmarks\, learning feedback models that guide inference-time reasoning\, and studying how multimodal systems can adapt through experience. We instantiate this agenda through two completed works and two proposed directions. Unicorn evaluates safety and robustness under out-of-distribution and adversarial conditions\, revealing substantial vulnerabilities across 22 vision-language models. ViLBench studies vision-language process reward modeling as both an evaluation challenge and a mechanism for inference-time improvement\, showing that process-guided reasoning selection can improve reliability. Building on these foundations\, we further study test-time experience accumulation and explore reliable multimodal agents for GUI and computer-use tasks. Together\, my research aims to move beyond capability-driven progress alone\, toward multimodal AI systems whose reliability can be evaluated\, improved\, and tested in realistic deployment settings. \nEvent Host: Haoqin Tu\, Ph.D. Student\, Computer Science & Engineering \nAdvisor: Cihang Xie \nZoom: 964 1355 0550 \nPasscode: zWxU8A
URL:https://events.ucsc.edu/event/tu-h-cse-from-evaluation-to-adaptation-building-reliable-multimodal-intelligence/
CATEGORIES:Ph.D. Presentations
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LOCATION:
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260526T103000
DTEND;TZID=America/Los_Angeles:20260526T123000
DTSTAMP:20260512T164007Z
CREATED:20260512T164007Z
LAST-MODIFIED:20260512T164007Z
UID:10014630-1779791400-1779798600@events.ucsc.edu
SUMMARY:Castro\, S. (CSE) - Agentic AI for Security: Adversarial Foundations for Autonomous Cyber Operations
DESCRIPTION:Autonomous Cyber Operations (ACO) agents promise effective security automation with minimal human intervention\, yet their deployment raises three interconnected challenges: agents must be realistic (reproducing diverse attacker sophistication)\, secure (preventing autonomy from becoming an attack surface)\, and feasible (safely replicating human behavior at full autonomy). \nWe argue that these three properties are requirements for ACO agents. Existing approaches do not address them together and lack diverse adversarial coverage\, formal threat models for attacks against the agents themselves\, and systematic evaluation of multi-agent topologies. \nWe advance all three ACO properties: (1) For realism\, we establish adversarial foundations by discovering Windows OS vulnerabilities and releasing two exploits reliable across XP through 11. (2) For security\, we formalize ACO meta-attacks and meta-defenses\, propose the first invariant-based Meta-IDS detecting both sensor and actuator meta-attacks\, and introduce the first hybrid LLM–RL ACO integration for defense with a novel inter-agent communication protocol. (3) For feasibility\, we present MaLO\, the first dynamic-topology multi-agent ACO system\, achieving a 78.6\% success rate across a new 42-task security benchmark and solving operations up to 40× faster than human experts. We further propose the Security Operation Complexity Index (SOCX) classification and the T×V×O taxonomy as the first objective-driven evaluation methodology for coding-agent attacks. \nTogether\, these contributions demonstrate that ACO agents can match real-world adversarial sophistication\, resist meta-attacks\, and outperform human operators on complex security tasks. Open challenges remain in adaptive adversaries\, LLM–RL co-training\, dynamic topology selection\, and deployment beyond simulated environments. \n  \nEvent Host:  Sebastián R. Castro\, PhD Candidate\, Computer Science & Engineering \nAdvisor: Alvaro A. Cárdenas \nZoom: https://ucsc.zoom.us/j/2267557290?pwd=S0dNTTV3emZGUzlqV3dLbTg3a0NFUT09&omn=92791061627 \nPasscode: G20c06
URL:https://events.ucsc.edu/event/castro-s-cse-agentic-ai-for-security-adversarial-foundations-for-autonomous-cyber-operations/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260526T100000
DTEND;TZID=America/Los_Angeles:20260526T110000
DTSTAMP:20260518T190031Z
CREATED:20260518T185313Z
LAST-MODIFIED:20260518T190031Z
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SUMMARY:Harsh\, B. (CSE) - SUPERSCALAR\, MULTIPLE TAKEN BRANCH PREDICTOR
DESCRIPTION:This work addresses improvements in branch prediction mechanism to support high perfor-\nmance processors. The state of the art aims to balance the prediction latency and prediction\naccuracy using multi level correcting predictors [27]. Prior published work focusses on scalar\ndesigns and prediction accuracy improvement for hard to predict branches employing tailor\nmade\, non generic and non transferrable solutions [8]. Recent work also proposes ahead pre-\ndiction [42–44] to solve the problem of low accuracy of L0 predictor. \nThis work proposes efficent\, generic and transferrable solutions to reduce mispredic-\ntions and to use the fetch bandwidth more efficiently. This includes a biased overriding multi-\nlevel hierarchy with three predictor levels (L0\, L1\, L2). L0 uses a High-Confidence-Only Taken\n(HOTP) predictor that only predicts high-confidence taken control-flow instructions. This work\nfurther uses L1-L2 biased training to decrease mispredictions by L2 while it trains on branches\non which L1 has reached high confidence. This work proposes a superscalar predictor built\nusing the state of the art scalar predictor. Superscalar predictor is implemented by sizing a su-\nperscalar TAGE variant (BATAGE) using Optuna-based search. with varying table sizes and\naspect ratios. The work further proposes a branch predictor frontend design (nTakenBP) to de-\nliver multiple taken branch predictions per cycle. Unlike prior work\, nTakenBP achieves this by\nextending the existing BTB and TAGE tag-comparison logic rather than deepening lookahead. \n  \nEvent Host: Bhawandeep Singh Harsh\, Ph.D. Candidate\, Computer Science & Engineering \nAdvisor: Jose Renau \nZoom: https://ucsc.zoom.us/j/4166778865?pwd=cS9NcnVjRjArYlRRcDcrY3d5N0ZKQT09
URL:https://events.ucsc.edu/event/harsh-b-cse-superscalar-multiple-taken-branch-predictor/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260521T090000
DTEND;TZID=America/Los_Angeles:20260521T143000
DTSTAMP:20260326T204610Z
CREATED:20260326T204610Z
LAST-MODIFIED:20260326T204610Z
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SUMMARY:Annual BE Student Project Showcase
DESCRIPTION:Join Baskin Engineering for our annual Student Project Showcase to celebrate the innovative work and accomplishments of undergraduate engineers in capstone courses and research pathways. The broader campus community\, parents\, and industry partners are invited to view the culmination of student work. \nThe day begins with oral presentations from nominated “best-in-class” teams and those working on industry-sponsored projects. Following this\, all students will participate in a comprehensive Poster Session featuring project outcomes with some teams including table-top demonstrations of functional hardware. \nEvent Details: \n\nDate: May 21\, 2026\nOral Presentations (Nominated/Industry Teams): 9:00 AM to 11:00 AM\, Engineering 2\, Room 180\nPoster Session (All Student Teams): 11:30 AM to 2:30 PM\, Engineering Courtyard
URL:https://events.ucsc.edu/event/be-student-project-showcase-2026/
CATEGORIES:Lectures & Presentations,Undergraduate
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260520T110000
DTEND;TZID=America/Los_Angeles:20260520T121500
DTSTAMP:20260518T155149Z
CREATED:20260518T155149Z
LAST-MODIFIED:20260518T155149Z
UID:10014650-1779274800-1779279300@events.ucsc.edu
SUMMARY:CSE Colloquium - Safety Alignment of LMs via Non-cooperative Games
DESCRIPTION:Presenter: Arman Zharmagambetov\, Meta \nAbstract:\nEnsuring the safety of language models (LMs) while maintaining their usefulness remains a critical challenge in AI alignment. Current approaches rely on sequential adversarial training: generating adversarial (harmful) prompts and fine-tuning LMs to defend against them. We introduce a different paradigm: framing safety alignment as a non-zero-sum game between an Attacker LM and a Defender LM trained jointly via online reinforcement learning. Each LM continuously adapts to the other’s evolving strategies\, driving iterative improvement. Our method uses a preference-based reward signal derived from pairwise comparisons instead of point-wise scores\, providing more robust supervision and potentially reducing reward hacking. Our RL recipe\, AdvGame\, shifts the Pareto frontier of safety and utility\, yielding a Defender LM that is simultaneously more helpful and more resilient to adversarial attacks. In addition\, the resulting Attacker LM converges into a strong\, general-purpose red-teaming agent that can be directly deployed to probe arbitrary target models. \nBio:\nArman Zharmagambetov is a research scientist in the Fundamental AI Research (FAIR) team at Meta. His research primarily focuses on machine learning and optimization\, recently exploring their application in enhancing the security and robustness of AI systems. He received his PhD from the University of California – Merced. Afterward\, he completed his postdoctoral research at FAIR\, focusing on Reinforcement Learning\, AI-guided design and Optimization. \nHosted by: Professor Alvaro Cardenas and Professor Sungjin Im \nDate and Time: Wednesday\, May 20\, 2026 from 11:00 am – 12:15 pm \nLocation: Engineering 2\, Room E2-180 (Refreshments such as fruit\, pastries\, coffee\, and tea will be provided.) \nZoom Option: https://ucsc.zoom.us/j/93445911992?pwd=YkJ2TQtF79h0PcNXbEcpZLbpK0coiY.1&jst=3
URL:https://events.ucsc.edu/event/cse-colloquium-safety-alignment-of-lms-via-non-cooperative-games/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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DTSTART;TZID=America/Los_Angeles:20260519T100000
DTEND;TZID=America/Los_Angeles:20260519T120000
DTSTAMP:20260512T163057Z
CREATED:20260512T163057Z
LAST-MODIFIED:20260512T163057Z
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SUMMARY:Paul Pena\, D. (CSE) - Efficient Pattern Counting in Sparse Graphs and Hypergraphs
DESCRIPTION:Pattern counting is a fundamental problem in computer science with applications in many domains. For a fixed small pattern H\, we are given a large graph G and we are asked to count the number of subgraphs or homomorphisms (edge-preserving maps) of H in G. For practical applications where the input graph can be very large\, we are interested in finding efficient algorithms\, that is\, algorithms that run in linear or subquadratic time with respect to the size of the input. \nFinding such algorithms in general (when G can be any graph) is not possible. Instead\, we restrict our input to sparse classes of graphs. One family of graph classes that has been widely studied in the context of subgraph and homomorphism counting is bounded-degeneracy graph classes. Real-world graphs in many domains have bounded degeneracy\, so studying these classes in theory can lead to practical algorithms. \nA series of advances in the study of homomorphism counting led to a dichotomy theorem that exactly characterized which patterns were linear-time computable for bounded-degeneracy inputs. This dissertation builds on this result\, extending it to other variants of this problem\, and generalizing it to other different settings\, like counting hypergraphs and notions of sparsity beyond degeneracy. \nOur results help develop the theory of subgraph counting in sparse graphs and hypergraphs\, and showcase how sparsity can be used both in theory and practice to develop faster algorithms. \n  \nEvent Host: Daniel Paul Pena\, Ph.D. Candidate\, Computer Science & Engineering  \nAdvisor: C. Sheshadhri \nZoom: https://ucsc.zoom.us/j/97685906168?pwd=O35brsWilyn2m8AgMn0dKgALBe6wi1.1
URL:https://events.ucsc.edu/event/paul-pena-d-cse-efficient-pattern-counting-in-sparse-graphs-and-hypergraphs/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260515T180000
DTEND;TZID=America/Los_Angeles:20260516T180000
DTSTAMP:20260508T194542Z
CREATED:20260428T221013Z
LAST-MODIFIED:20260508T194542Z
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SUMMARY:NemoClaw NVIDIA x ASUS Hackathon @ UC Santa Cruz
DESCRIPTION:Welcome to the premier physical AI hackathon on the West Coast. We are bringing together the top 200 AI\, infrastructure\, and hardware engineers to build autonomous\, agentic applications on the NVIDIA NemoClaw stack. \n​You aren’t just calling APIs\, you are building on enterprise-grade hardware. \n​The Tracks: \n\nThe Edge Track: 40 exclusive teams will be granted physical\, on-site access to an ASUS DGX Spark unit to build and deploy locally.\n​The Cloud Track: Teams will build the exact same stack utilizing fully sponsored cloud compute instances via Brev.dev.\n\n​The Arsenal & Prizes: Every team builds on a unified playing field. The top projects will take home heavy enterprise hardware\, including: \n\n​NVIDIA Jetson Orin Nanos\n​The ASUS Ascent (DGX Spark)\n​Jensen Huang signed NVIDIA hats & premium swag\n​High-value Brev.dev compute credits\n​Monitors\n​Internship Opportunities\n\n​The Details: \n\n​Who: Open to the top engineers at UC Santa Cruz and local feeder universities.\n​Food: Fully catered for 24 hours. Energy\, caffeine\, and meals are on us.\n​Special Guests*: Opening and closing ceremonies featuring VIP industry leaders (to be announced).\n​Title Sponsors: Nvidia\, ASUS\, Baskin School of Engineering\n\nRegister today!  \n​Space is strictly capped at 200 builders. Registration requires application approval. \n*May subject to change \n 
URL:https://events.ucsc.edu/event/nvidia-hackathon-2026/
LOCATION:Kresge College\, R-3 Suites\, Santa Cruz\, CA\, 95064
CATEGORIES:Competition,Meetings & Conferences
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260515T130000
DTEND;TZID=America/Los_Angeles:20260515T160000
DTSTAMP:20260429T224549Z
CREATED:20260306T005653Z
LAST-MODIFIED:20260429T224549Z
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SUMMARY:STEM Culture Festival
DESCRIPTION:The STEM Culture Festival is returning to UC Santa Cruz on Friday\, May 15 from 1-4pm in the Baskin Engineering Courtyard. Join us! \nThis year\, we’re expanding with even more performances\, activities\, and creative ways to celebrate UCSC’s vibrant\, diverse\, and excellent STEM culture!  \nWhat to expect: \n\nCuban Dance Master Susana Arenas and her troupe of Orisha dancers led by Cuban Drum Master Toribio Garcia return for a rousing\, communal dance\n\nStudent performers: Los Mejicas and their traditional baile folklórico followed by an open dance lesson/performance by Slug N’ Boots\n\nSTEM-themed drag performances and spoken word poetry by student creatives \n\nAssociate Vice Chancellor for Student Success and Equity Dr. Ebonee Williams (Chemical Engineering\, University of Washington ‘04) will share an inspirational talk on “Bringing our whole selves to STEM!”\n\nEl Buen Taco and Falafel Santa Cruz will be serving delicious food\, completely FREE for all attendees who engage with the student orgs and their activities\n\nMore than just your standard student organization tabling: Games\, interactive demos\, culturally themed activities\, and opportunities to learn more about clubs from all over campus \n\nRaffle for gift cards to be awarded every hour from 1-4pm – must be present to win! \n\nThis event will take place in the Baskin Engineering Courtyard and will be open to all UCSC students\, staff\, and faculty. \nThe STEM Culture Festival celebrates and elevates the many backgrounds\, cultures\, and identities that intersect with our work as scientists\, engineers\, educators\, and members of the UCSC community. It is a rare opportunity when all of UCSC is invited to meet at the engineering school for a time of joy and togetherness. We enthusiastically invite you to attend and be in community with us – especially now in these tumultuous times of division and disunity.  \nThis event represents a collaboration between Baskin Engineering\, the Women’s Center\, the Lionel Cantú Queer Resource Center\, El Centro Latinx and Chicanx Resource Center\, the Asian American and Pacific Islander Resource Center\, the Physical and Biological Sciences Division\, and the Genomics Institute.
URL:https://events.ucsc.edu/event/stem-culture-festival-2026/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Concerts,Performances,Social Gathering,Undergraduate
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260514T170000
DTEND;TZID=America/Los_Angeles:20260514T190000
DTSTAMP:20260422T164712Z
CREATED:20260420T170937Z
LAST-MODIFIED:20260422T164712Z
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SUMMARY:QB3/QBI Pre-Hackathon Mixer
DESCRIPTION:Join us for an exciting pre-hackathon mixer at University of California\, Santa Cruz! Get ready to mingle\, form teams\, and start brainstorming ideas for your projects before the QBI Hackathon kicks off at UCSF in June 2026. \nAgenda\n5:00 PM – Doors Open\n5:30 PM – Pitch Session\n6:00 PM – Networking & Mingling \nWe can’t wait to see the ideas and projects that will be presented at the mixer. Whether you’re presenting or simply attending to learn more and meet potential teammates\, this event is an excellent opportunity to start building connections within our vibrant community of participants. \nDon’t miss out on this chance to get inspired and kickstart your hackathon experience. To attend\, please RSVP  – https://qbi.ucsf.edu/events/hackathon-mixer-ucsc-2026 \nThe QBI hackathon is a 48-hour event connecting the developer community in the Bay Area with the scientists from the three QB3 campuses (UCSF\, UCB and UCSC)\, during which we work together on cutting edge biomedical problems. One of the highlights of our pre-hackathon mixer is the opportunity for participants to showcase their ideas\, projects\, or concepts to the group.
URL:https://events.ucsc.edu/event/qb3-qbi-pre-hackathon-mixer/
LOCATION:Rachel Carson College\, 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Meetings & Conferences,Reception
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260514T090000
DTEND;TZID=America/Los_Angeles:20260514T110000
DTSTAMP:20260427T162920Z
CREATED:20260427T162713Z
LAST-MODIFIED:20260427T162920Z
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SUMMARY:Shadmon\, R. (CS) - Proximal Byzantine Agreement
DESCRIPTION:Research on fault-tolerance protocols for approximate Byzantine agreement\n(ABA) has largely focused on ensuring that distributed processes remain\nconsistent despite fewer than 1/3 faulty processes. Yet in many\nreal systems\, consistency is only useful when it enables processes to\nmake accurate decisions from replicated\, noisy\, and potentially\nadversarially corrupted data relative to an ideal fault-free baseline.\nThis limitation is increasingly important in edge applications such as\nautonomous vehicles\, drone networks\, smart cities\, manufacturing\, and\nsensor-based systems\, where agreement directly drives downstream\nactions. At the same time\, many existing ABA protocols impose\nimpractical requirements\, such as replica counts that grow with data\ndimensionality or prior knowledge of the maximum distance between values\nproposed by each process. \nWe introduce Stochastic Byzantine Agreement (SBA)\, a new problem\nformulation in which the goal is to estimate an output from n replicated\nvalues consisting of n-f nonfaulty outputs generated by an\nunderlying stochastic process and f arbitrarily chosen\nByzantine outputs. We then present Proximal Byzantine Agreement\n(PBA)\, a stochastic agreement protocol that solves SBA by enabling\nconsumers to infer the most likely ideal output conditioned on the\noutputs they receive. In addition\, PBA provides a region\nguarantee that\, as we prove\, always contains the corresponding\nfault-free stochastic estimate of the true value. \nWe describe the design of PBA\, formalize its guarantees\, and evaluate\nits accuracy against existing techniques using stochastic simulations\nacross symmetric and asymmetric distributions and multiple system\nconfigurations. We also evaluate runtime overhead and performance in a\nfollow-the-leader drone network simulator and in a Java implementation on\nRaspberry Pis using a real-world adaptive cruise control dataset. Our\nresults show that PBA performs competitively across all evaluated\nsettings and especially well under simulated Byzantine attack. Most\nnotably\, PBA maintains stable accuracy as dimensionality increases\,\noutperforming methods that require up to 10x more replicas}\nand incur up to 10x greater computation time per agreement\ndecision. \nEvent Host: Roy Shadmon\, Ph.D. Candidate\, Computer Science  \nAdvisor: Owen Arden \nZoom: https://ucsc.zoom.us/j/98390167664?pwd=DwkNuUSRaZRKXYb7pQbDYXgf7HFFPg.1 \nPasscode: pba
URL:https://events.ucsc.edu/event/shadmon-r-cs-proximal-byzantine-agreement/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260513T150000
DTEND;TZID=America/Los_Angeles:20260513T170000
DTSTAMP:20260501T203636Z
CREATED:20260501T203636Z
LAST-MODIFIED:20260501T203636Z
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SUMMARY:Zheng\, K. (CSE) - Towards Generalist Embodied World Models: From Neuro-Symbolic Interaction to Self-Evolving 3D World Generation
DESCRIPTION:Artificial intelligence is moving beyond passive perception toward systems that can understand\, interact with\, and generate the world. This dissertation studies generalist embodied world models that connect language\, vision\, action\, and 3D scene representations. It explores how multimodal systems can ground human instructions in physical environments\, reason over long-horizon tasks\, generate coherent text-and-visual content\, and construct spatially consistent 3D worlds from limited observations. Across embodied reasoning\, multimodal generation\, and 3D world construction\, this dissertation develops methods that combine pretrained models with structured interfaces such as symbolic reasoning\, generative visual tokens\, spatial priors\, and iterative self-refinement. These approaches aim to improve generalization\, data efficiency\, interpretability\, and geometric consistency without relying solely on monolithic end-to-end training. Together\, the work argues for a broader view of embodied AI: intelligent systems should not only recognize or describe the world\, but also act within it\, imagine it\, and build reusable representations of it. \nEvent Host: Kaizhi Zheng\, Ph.D. Candidate\, Computer Science & Engineering  \nAdvisor: Xin Eric Wang \n  \nZoom: https://ucsc.zoom.us/j/91912825272?pwd=aps1YHcJKMaqmhtgl72f51K9EbxrHt.1 \nPasscode: 991132
URL:https://events.ucsc.edu/event/zheng-k-cse-towards-generalist-embodied-world-models-from-neuro-symbolic-interaction-to-self-evolving-3d-world-generation/
CATEGORIES:Ph.D. Presentations
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LOCATION:
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260513T110000
DTEND;TZID=America/Los_Angeles:20260513T121500
DTSTAMP:20260330T203417Z
CREATED:20260330T203158Z
LAST-MODIFIED:20260330T203417Z
UID:10011814-1778670000-1778674500@events.ucsc.edu
SUMMARY:CSE Colloquium - The EU’s Cybersecurity Framework: what it is\, what it means
DESCRIPTION:Presenter: Chris Jay Hoofnagle\, Frederik Zuiderveen Borgesius\, Lothar Determann\, Pieter T.J. Wolters \nAbstract: \nThe European Union has enacted a comprehensive cybersecurity framework (the “Framework”) that imposes far-reaching obligations on developers of standalone software and connected products. This Article describes the European legislative approach before turning to a description of the Framework. Anchored by the Cyber Resilience Act and the Cybersecurity Act\, and reinforced by a constellation of sector-specific measures\, the Framework effectively creates a California-like-products-liability regime for software. It mandates extensive security-by-design obligations\, imposes stringent conformity assessment and incident-reporting duties\, and shifts substantial compliance burdens onto manufacturers\, importers\, and distributors. It even treats emotional wrongs caused by software as injurious. The Framework will take full effect in December 2027\, meaning that companies must integrate its requirements into their current product cycles. \nBio: Chris Hoofnagle is professor of law in residence at the University of California\, Berkeley\, where he teaches tort law and cybersecurity. \nHosted by: Professor Alvaro Cardenas \nLocation: Engineering 2\, Room E2-180 (Refreshments such as fruit\, pastries\, coffee\, and tea will be provided.) \nZoom Option: https://ucsc.zoom.us/j/93445911992?pwd=YkJ2TQtF79h0PcNXbEcpZLbpK0coiY.1&jst=3
URL:https://events.ucsc.edu/event/cse-colloquium-the-eus-cybersecurity-framework-what-it-is-what-it-means/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260512T100000
DTEND;TZID=America/Los_Angeles:20260512T120000
DTSTAMP:20260421T160759Z
CREATED:20260421T160759Z
LAST-MODIFIED:20260421T160759Z
UID:10013625-1778580000-1778587200@events.ucsc.edu
SUMMARY:Chen\, Q. (CSE) - New Approximation and Online Algorithms using Novel Combinatorial Structures
DESCRIPTION:Most optimization problems face the challenge of computing an optimum solution requiring superpolynomial time. In particular\, they are classified as NP-hard problems that have no polynomial-time algorithm to date. Instead\, computer scientists turn to find an approximate solution and create numerous elegant algorithms. However\, in the modern era\, computational environments have changed drastically\, and we are not able to afford to design new algorithms for each new problem via repeated trial and error. Therefore\, systematic ways to understand the possibilities and limitations of these problems are desired. This dissertation studies several central combinatorial optimization problems\, focusing on understanding the key structural obstacles and developing unified frameworks. Mainly\, we study two types of combinatorial optimization problems:\n(1) Scheduling. The problem is associated with limited resources\, and our target is to find an allocation method to complete all jobs over time that minimizes the overall budget cost.\n(2) Network Design. Different from scheduling problems. In this problem\, we aim to find a minimum-cost topological network that supports routing for demanding communications. \nOur first work is focused on a group-to-group survivable network design problem that generalizes the classic point-to-point network to support routing between any pair of subsets of nodes. Previous research stops at limited faults\, and the difficulty comes from the way to compress the graph into a tree. We propose a new framework via capacitated tree embeddings against arbitrary faults in the network\, which gives the first polylogarithmic approximation algorithm. Further\, this framework captures nearly all the recent models proposed in the area. \nIn contrast to the offline optimization problems mentioned above\, online algorithms are natural adaptations that have been found in tremendous real applications. In online algorithms\, the algorithm wants to compete against arbitrary uncertainty\, which means the instance is unknown at first and revealed over time. We study various scheduling problems and focus on some important metrics – average flow time\, which measures the average time a job stays in the system from its arrival to completion. Real-world demands give online scheduling problems enormously different settings. Computer scientists need to repeat errors and trials to find a provably good solution. We find the key required combinatorial property is supermodularity for the residual objective\, which measures the average completion time for all alive jobs assuming they have the same arrival time. Further\, we relate supermodularity with gross-substitute/linear-substitute (GS/LS)\, which is a well-studied definition in economics. Finally\, we propose a meta-algorithm that solves all captured problems in one shot. In the end\, we revisit the proportional fairness (PF) algorithm for $L_p$-norms of flow time. By reinterpreting the previous potential function and the corresponding Fisher market\, we show that PF is competitive. \n  \nEvent Host: Qingyun Chen\, Ph.D. Candidate\, Computer Science & Engineering  \nAdvisor: Sungjin Im \nZoom: https://ucsc.zoom.us/j/92628493495?pwd=iJq8YwarrYyofPLF4AmZpwzsZnLyvt.1 \n 
URL:https://events.ucsc.edu/event/chen-q-cse-new-approximation-and-online-algorithms-using-novel-combinatorial-structures-2/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260506T110000
DTEND;TZID=America/Los_Angeles:20260506T121500
DTSTAMP:20260505T154459Z
CREATED:20260505T154459Z
LAST-MODIFIED:20260505T154459Z
UID:10014548-1778065200-1778069700@events.ucsc.edu
SUMMARY:CSE Colloquium - The Wallenberg AI\, Autonomous Systems and Software Program
DESCRIPTION:Presenters: Prof. Karl-Erik Arzen (Co-Director of WASP and Lund University)\, Dr. Paul Townend (WASP Graduate School management and Umeå University)\, and Carl Magnus Bruhner (Linkoping University) \nAbstract: The Wallenberg AI\, Autonomous Systems\, and Software Program (WASP) is the largest research initiative in Swedish history\, with a budget of over $700M and a research focus AI and autonomous systems acting in collaboration with humans. The program funds over 500 current PhD students\, has recruited over 70 international faculty\, engages with over 80 companies and organizations\, and has formal agreements with academic organizations including Stanford\, UC Berkeley\, MIT\, Caltech\, ETH Zurich\, and Imperial College London. \nAs part of its internationalization efforts\, WASP has organized a visit to the Bay Area for 13 PhD students and 2 faculty – all of whom specialize in Cloud and AI systems and software. Topics studied by the students include modeling and predicting network dynamics\, verification and accountability in agentic AI systems\, using underwater robotic systems to inspect and maintain subsea data infrastructures\, compliance engineering with the EU AI act\, runtime requirements conflict management in AI-driven autonomous systems\, and cloud-native traffic management for mobile networks. \nBio: The talk will be led by Prof. Karl-Erik Arzen (Co-Director of WASP and Lund University)\, Dr. Paul Townend (WASP Graduate School management and Umeå University)\, and Carl Magnus Bruhner (Linkoping University). We will present the program in detail\, and discuss potential opportunities for collaboration and future research visits from our students. More information on WASP can be found at: https://wasp-sweden.org \nHosted by: Professor Alvaro Cardenas \nDate and Time: Wednesday\, May 6 from 11:00 am – 12:15 pm \nLocation: Engineering 2\, Room E2-180 (Refreshments such as fruit\, pastries\, coffee\, and tea will be provided.) \nZoom Option: https://ucsc.zoom.us/j/93445911992?pwd=YkJ2TQtF79h0PcNXbEcpZLbpK0coiY.1&jst=3
URL:https://events.ucsc.edu/event/cse-colloquium-the-wallenberg-ai-autonomous-systems-and-software-program/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260429T110000
DTEND;TZID=America/Los_Angeles:20260429T121500
DTSTAMP:20260402T185047Z
CREATED:20260402T185047Z
LAST-MODIFIED:20260402T185047Z
UID:10011848-1777460400-1777464900@events.ucsc.edu
SUMMARY:CSE Colloquium - Towards Safe and Resilient Large-scale Distributed Programming
DESCRIPTION:Presenter: Philipp Haller\, KTH Royal Institute of Technology \nAbstract: \nDistributed programming is notoriously difficult. Not only are distributed systems concurrent\, they pose additional challenges including data consistency and fault tolerance. At the same time\, the share of software systems that are necessarily distributed systems is growing rapidly. As a result\, too many software developers are asked to become distributed systems experts. Thus\, tools and techniques for ensuring the correctness of distributed systems are urgently needed in order to leave this unsustainable trajectory. This talk presents research results towards the design and implementation of programming systems that support emerging applications and workloads; provide reliability and trust; and embrace simplicity and accessibility. Concretely\, the presented work focuses on two directions. \nThe first direction explores a distributed programming model that provides consistency while enabling high availability for workloads operating on join-semilattices without sacrificing partition tolerance. We propose a new consistency protocol\, called observable atomic consistency protocol (OACP)\, which leverages on-demand coordination to support both coordination-free operations as well as totally-ordered operations on replicated data types. We present a formal\, mechanized model of OACP in rewriting logic and verify key correctness properties using the model checking tool Maude. Furthermore\, we present the evaluation of a prototype implementation of OACP based on Akka\, a widely-used actor-based middleware. The second direction explores a programming system that aims to reconcile the scalability and fault tolerance of stream processing systems with the flexibility of the actor concurrency model. The programming system ensures a failure-transparency property\, effectively masking failures through transparent recovery. Our work is the first to formalize failure transparency using a small-step operational semantics\, and to provide proofs of failure transparency for stateful dataflow streaming and a fault-tolerant actor-based programming model. \nBio: \nPhilipp Haller is an Associate Professor in the School of Electrical Engineering and Computer Science (EECS) at KTH Royal Institute of Technology in Stockholm\, Sweden. His main research interests are in the design and implementation of programming languages\, type systems\, concurrency\, and distributed programming. He was part of the team that received the 2019 ACM SIGPLAN Programming Languages Software Award for the development of the Scala programming language. Prior to KTH\, he was an early employee at Akka (previously Lightbend\, Inc.)\, a start-up company developing and supporting Scala as well as frameworks for large-scale distributed programming. Prior to Akka\, he was a post-doctoral fellow at Stanford University\, USA\, and at EPFL\, Switzerland. In 2010 he received his PhD in computer science from EPFL\, including a nomination for the 2010 EPFL Doctorate Award. In 2006 he received his Dipl.-Inform. degree from Karlsruhe Institute of Technology (previously University of Karlsruhe)\, Germany. \nHosted by: Professor Mohsen Lesani \nLocation: Engineering 2\, Room E2-180 (Refreshments such as fruit\, pastries\, coffee\, and tea will be provided.) \nZoom Option: https://ucsc.zoom.us/j/93445911992?pwd=YkJ2TQtF79h0PcNXbEcpZLbpK0coiY.1&jst=3
URL:https://events.ucsc.edu/event/cse-colloquium-towards-safe-and-resilient-large-scale-distributed-programming/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260427T110000
DTEND;TZID=America/Los_Angeles:20260427T130000
DTSTAMP:20260423T210320Z
CREATED:20260420T225301Z
LAST-MODIFIED:20260423T210320Z
UID:10012119-1777287600-1777294800@events.ucsc.edu
SUMMARY:Quality First Coding Contest
DESCRIPTION:This is a programming contest\, but with a twist! Instead of scoring you based on your speed and solution accuracy\, we score you based on your programming quality and solution accuracy. This means that instead of looking at how fast you can program a solution\, we look at your number of compiles/runs instead.* The contestant that uses the least number of compiles/runs to produce passing code is the winner. Ties are broken by time. \nFood will be provided. QFCC 20260427 – Poster
URL:https://events.ucsc.edu/event/quality-first-coding-contest/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260423T180000
DTEND;TZID=America/Los_Angeles:20260423T193000
DTSTAMP:20260402T222539Z
CREATED:20260402T213440Z
LAST-MODIFIED:20260402T222539Z
UID:10012030-1776967200-1776972600@events.ucsc.edu
SUMMARY:Climate Week Tech Connect: Energy Solutions
DESCRIPTION:Join Baskin Engineering to explore the frontier of power engineering\, where the rapid rise of electrification and digital infrastructure is creating an unprecedented demand for next-generation talent and a critical opportunity for sustainability.  \nThis networking event bridges the gap between the classroom and the field\, offering students and faculty a front-row seat to the trends and high-impact career opportunities shaping our energy future. The event is part of Baskin Engineering Climate Week\, focused on raising awareness of climate issues and sustainability research and teaching. \nWhere: BE Courtyard\nWhen: Thursday\, April 23\, 6:00-7:30 p.m. \nWe hope to see you there!
URL:https://events.ucsc.edu/event/climate-week-tech-connect-energy-solutions/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Meetings & Conferences
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260423T170000
DTEND;TZID=America/Los_Angeles:20260423T181500
DTSTAMP:20260402T212222Z
CREATED:20260402T211703Z
LAST-MODIFIED:20260402T212222Z
UID:10011935-1776963600-1776968100@events.ucsc.edu
SUMMARY:Careers in Climate Tech & Sustainability
DESCRIPTION:Ready to explore career pathways that matter? \nAttend our very special Careers in Climate Tech & Sustainability Panel—celebrating Baskin Engineering Climate Week—for an inside look at careers that will help build a sustainable future. Panelists representing different roles and organizations will share their career journeys and offer practical insights into working in climate tech. There will also be a catered networking reception that follows—don’t miss it! \nGet informed\, inspired\, and discover your path to a career in sustainability! \nThis event is part of Baskin Engineering’s Climate Tech Day featuring a community fair where students\, faculty\, climate and sustainability tech companies\, and community organizations will showcase their works through demonstrations\, poster presentations\, tabling\, and more.  \nWhere: E2-180\nWhen: Thursday\, April 23\, 5:00-6:15 p.m. \nRegister via Handshake. \nIf you have disability-related needs\, please contact the Career Success office at csuccess@ucsc.edu or (831) 459-4420 as soon as possible. \nYOU BELONG HERE\nPrograms and services are open to all\, consistent with state and federal law\, as well as the University of California’s nondiscrimination policies. Every initiative—whether a student service\, faculty program\, or community event—is designed to be accessible\, inclusive\, and respectful of all identities. To learn more\, please visit UC Nondiscrimination Statement or Nondiscrimination Policy for UC Publications.
URL:https://events.ucsc.edu/event/careers-in-climate-tech-sustainability/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260423T140000
DTEND;TZID=America/Los_Angeles:20260423T170000
DTSTAMP:20260403T220700Z
CREATED:20260403T215527Z
LAST-MODIFIED:20260403T220700Z
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SUMMARY:Climate Tech & Sustainability Showcase
DESCRIPTION:Join us for a Climate Tech & Sustainability Showcase\, where students\, faculty\, climate and sustainability-focused companies\, founders\, and community organizations come together to share their work and ideas. The event is part of Baskin Engineering Climate Week\, focused on raising awareness of climate issues and sustainability research and teaching. \nExplore a range of interactive demos\, poster presentations\, and tabling displays highlighting innovative research\, emerging technologies\, and real-world solutions to climate challenges. Baskin Engineering student organizations will also be on hand to share their climate friendly projects! \nCome network\, promote your organization\, and meet up-and-coming talent alongside other passionate\, like-minded members of the climate and sustainability community. \nWhere: BE Courtyard\nWhen: 2:00-5:00 p.m.
URL:https://events.ucsc.edu/event/climate-tech-sustainability-showcase/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260422T110000
DTEND;TZID=America/Los_Angeles:20260422T121500
DTSTAMP:20260401T165930Z
CREATED:20260331T171056Z
LAST-MODIFIED:20260401T165930Z
UID:10011819-1776855600-1776860100@events.ucsc.edu
SUMMARY:CSE Colloquium - Robust Machine Learning for Biomedical Data: Efficiency\, Reliability\, and Generalizability
DESCRIPTION:Presenter\nChenyu You\, Stony Brook University \nAbstract\nIn the rapidly growing area of machine learning\, there is profound promise in crafting intelligent\, data-driven methods for diverse real-world applications. Yet\, in safety-critical domains like healthcare\, some fundamental challenges remain: (1) The insufficiency of raw biomedical data emphasizes the need for data-efficient and robust learning approaches. (2) The imperative of safety and stability necessitates a cohesive framework that unifies learning with theoretical guarantees. (3) The inherent heterogeneity and distribution shifts in real-world clinical data call for robust and generalizable learning methods. To address these challenges\, there are several major directions I have explored: (i) (Robust) Machine Learning for Imperfect Medical Data: The development of machine learning models\, particularly in the context of label scarcity\, increasingly necessitates the collection of substantial annotated medical data. Moreover\, medical data often display a long-tailed class distribution\, which consequently results in notable imbalance issues. To this end\, there are several growing interests in training machine learning models jointly across imbalanced class distributions and limited annotations. I have developed novel\, efficient\, statistically consistent algorithms to improve empirical performance for biomedical image analysis. (ii) Learning with Theoretical Guarantees: As machine learning methods have become ubiquitous in clinical decision-making\, their reliability and interpretability have become important. This is particularly crucial in the field of biomedical image analysis\, where decision outcomes can have profound implications. I have developed novel machine learning algorithms that enable provably accurate anatomical modeling with theoretical guarantees. (iii) Generalize across Diverse Biomedical Data: The development of medical foundation models often requires massive and diverse biomedical data. To this end\, I have developed various foundation models for biomedical imaging data and explored novel applications of these models. I have also developed novel medical AI Agents that lead to the scalable and accurate predictive modeling\, particularly for distribution shift problems. \nSpeaker Bio\nChenyu You is an Assistant Professor in the Department of Applied Mathematics & Statistics and Department of Computer Science at Stony Brook University. He is also the core faculty member of the CVLab\, AI institute\, and affiliated with the Institute for Advanced Computational Science. His research focuses on both fundamental and applied problems in computer vision and machine learning\, often with a focus on generalization\, and making machine learning more reliable. Our applied research includes applications to healthcare\, biomedical imaging\, and cognitive neuroscience. He received his Ph.D. in 2024 from Yale University under the advisement of James S. Duncan\, his M.S. in 2019 from Stanford University under the advisement of Daniel Rubin\, and his B.S. in 2017 from Rensselaer Polytechnic Institute under the advisement of Ge Wang\, all in electrical engineering. He has also spent wonderful time at Facebook AI Research (FAIR)\, as well as Google Research. He serves on the Medical Image Computing and Computer-Assisted Intervention Society (MICCAI)\, and the SUNY AI Symposium Planning Committee\, and as associate editors for IEEE Transactions on Medical Imaging\, Medical Image Analysis\, IEEE Transactions on Neural Networks and Learning Systems\, Pattern Recognition\, and Transactions on Machine Learning Research. He has received AAAI’26 New Faculty Highlights\, CPAL’26 Rising Stars Award\, Tinker Research Grant Award\, Lambda Research Grant Award\, ICML’25 Oral Presentation Award\, EMBC’25 Top Paper Award\, MICCAI’25 NIH Registration Grant Award\, IEEE TMI’25 Distinguished Associate Editor Certificate of Excellence Award\, and Yale George P. O’Leary Graduate Fellowship\, and has been ranked as the World’s Top 2% most-cited scientists by Stanford University since 2024\, is a member of the Sigma Xi scientific research society\, and received the Excellence in Teaching Award for Spring and Fall 2025. For more information\, please check his website: https://chenyuyou.me/. \nHosted by: Professor Yuyin Zhou \nLocation: Engineering 2\, Room E2-180 (Refreshments such as fruit\, pastries\, coffee\, and tea will be provided.) \nZoom Option: https://ucsc.zoom.us/j/93445911992?pwd=YkJ2TQtF79h0PcNXbEcpZLbpK0coiY.1&jst=3
URL:https://events.ucsc.edu/event/cse-colloquium-robust-machine-learning-for-biomedical-data-efficiency-reliability-and-generalizability/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260421T100000
DTEND;TZID=America/Los_Angeles:20260421T113000
DTSTAMP:20260401T234645Z
CREATED:20260401T234645Z
LAST-MODIFIED:20260401T234645Z
UID:10011845-1776765600-1776771000@events.ucsc.edu
SUMMARY:BE Climate & Cookies Student Pop-Up!
DESCRIPTION:Come get excited about Baskin Engineering Climate Week at our student pop-up! 🌎 \nClimate Week is a chance to explore how Baskin Engineering is addressing climate challenges through innovative research\, teaching\, and hands-on projects. \nDiscover the events happening throughout the week and find ways to get involved! \nSwing by for FREE BE swag\, coffee\, cookies\, Climate Week stickers\, and more—first come\, first served! \nWhere: BE Courtyard\nWhen: Tuesday\, April 21\, 10:00-11:30 a.m. \nWe hope to see you there!
URL:https://events.ucsc.edu/event/be-climate-week-pop-up-2026/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Social Gathering
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260415T173000
DTEND;TZID=America/Los_Angeles:20260415T203000
DTSTAMP:20260402T171331Z
CREATED:20260325T220453Z
LAST-MODIFIED:20260402T171331Z
UID:10011772-1776274200-1776285000@events.ucsc.edu
SUMMARY:Kraw Lecture: At the Forefront of AI: Innovation and Discovery
DESCRIPTION:Artificial intelligence is transforming how we understand and solve the world’s most complex challenges—while at the same time causing new challenges and concerns. We invite you to join us for a special UC Santa Cruz Kraw Lecture showcasing the faculty whose groundbreaking research in artificial intelligence is transforming science\, technology\, and society. From advances in autonomous systems and natural language processing to the development of sustainable and responsible AI\, this conversation will highlight the innovative work taking place across disciplines and the real-world impact it is poised to have. \nModerated by special guest Ahmad Thomas\, CEO of the Silicon Valley Leadership Group (SVLG)\, this dynamic discussion will bring together leading researchers to explore how these technologies are shaping the future—accelerating discovery\, addressing complex global challenges\, and opening new frontiers for collaboration. Gain insight into the ideas\, discoveries\, and collaborations shaping the next generation of artificial intelligence research and hear from the leaders advancing this work.\n \n\n\nIn-Person Reception: 5:30 p.m.\nLecture: 6:15 p.m.\n\nRegister Now
URL:https://events.ucsc.edu/event/kraw-lecture-at-the-forefront-of-ai-innovation-and-discovery/
LOCATION:The Quad Conference Center\, 2400 Sand Hill Rd\, Menlo Park\, CA\, 94025\, United States
CATEGORIES:Lectures & Presentations
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260415T110000
DTEND;TZID=America/Los_Angeles:20260415T121500
DTSTAMP:20260407T155318Z
CREATED:20260407T155318Z
LAST-MODIFIED:20260407T155318Z
UID:10012050-1776250800-1776255300@events.ucsc.edu
SUMMARY:CSE Colloquium - Algorithmic Problems in Discrete Choice by Ravi Kumar
DESCRIPTION:Presenter: Ravi Kumar\, Google \nAbstract:\nIn discrete choice\, a user selects one option from a finite set of available alternatives\, a process that is crucial for recommendation systems applications in e-commerce\, social media\, search engines\, etc.  A popular way to model discrete choice is through Random Utility Models (RUMs).  RUMs assume that users assign values to options and choose the one with the highest value from among the available alternatives.  RUMs have become increasingly important in the Web era; they offer an elegant mathematical framework for researchers to model user choices and predict user behavior based on (possibly limited)  observations.   While RUMs have been extensively studied in behavioral economics and social sciences\, many basic algorithmic tasks remain poorly understood.  In this talk\, we will discuss various algorithmic and learning questions concerning RUMs. \nBio: \nRavi Kumar has been a research scientist at Google since 2012. Prior to this\, he was at the IBM Almaden Research Center and at Yahoo! Research. His interests include algorithms for massive data\, ML/privacy\, and the theory of computation. He maintains an extensive publication record that includes Test-of-Time Awards from STOC and WWW\, as well as Best Paper Awards from KDD and WWW\, to mention a few. He is an ACM fellow.\n\nHosted by: Professor Sungjin Im \n\nDate and Time: Wednesday\, April 15\, 2026 from 11:00 am – 12: 15 pm \nLocation: Engineering 2\, Room E2-180 (Refreshments such as fruit\, pastries\, coffee\, and tea will be provided.) \n\nZoom Option: https://ucsc.zoom.us/j/93445911992?pwd=YkJ2TQtF79h0PcNXbEcpZLbpK0coiY.1&jst=3 \n\n 
URL:https://events.ucsc.edu/event/cse-colloquium-algorithmic-problems-in-discrete-choice-by-ravi-kumar/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260414T140000
DTEND;TZID=America/Los_Angeles:20260414T160000
DTSTAMP:20260326T162922Z
CREATED:20260326T162922Z
LAST-MODIFIED:20260326T162922Z
UID:10011787-1776175200-1776182400@events.ucsc.edu
SUMMARY:Castello\, J. (CSE) - Space Mission Simulation From the Outside In
DESCRIPTION:Robotic space missions often use discrete event simulation to reduce risk in operation. A simulation applies a set of planned activities to a model of mission resources\, and the model’s observed behavior is used to predict real-world outcomes. However\, logically concurrent activities are typically simulated under one possible linearization of their events – an order that may not reflect the eventual reality. Some simulation systems provide mechanisms for controlling the order of events; but this is a solution to a self-imposed problem. We instead question the assumption causing this problem: that events are totally ordered to begin with. \nWe study Merlin\, an open-source simulator developed at Caltech’s Jet Propulsion Laboratory and designed by the author\, that exchanges the traditional total order of events for a *partial* order. Under this approach\, a resumed activity can only observe events that causally precede its resumption\, and concurrent events are reconciled under custom policies. However\, the resulting design is more complex (and less understood) than that of linearizing simulators\, obscuring its key insights. As such\, we have developed Eidolon: a compact core calculus for Merlin-style simulation whose operational semantics follows an “outside-in”\, substitution-based execution model. Although Eidolon is derived from the concepts present in Merlin\, we intend it to be a vehicle for exploring non-linearizing simulation in general. \nFirst\, we propose making Eidolon *incremental*: a change to the set of planned activities should not incur a full resimulation from scratch except in the worse case\, instead reusing any cached computations that are not sensitive to the change. Since mission planning is a highly iterative process involving many simulations and subsequent tweaks to the plan\, incremental resimulation may allow plans to be finalized in less time\, or allow higher-quality plans to be obtained in the same amount of time. The substitution-oriented approach of Eidolon is what makes this feasible\, since individual computations align cleanly with subtree boundaries. \nSecond\, in the spirit of Reynolds’ defunctionalization and Danvy’s rational reconstruction\, we propose developing a denotational semantics for Eidolon and demonstrating its mechanical conversion into an abstract machine. As a mathematical artifact\, Eidolon is designed for reasoning and legibility rather than efficiency; nonetheless\, defunctionalization allows us to *refactor* our semantics into something that stands a chance of being practical. In particular\, defunctionalization reifies the recursive structure of a denotational semantics into an explicit data structure. As a result\, the defunctionalized form of Eidolon will recover an explicit priority queue like that of traditional linearizing simulators\, but without their assumption of total ordering. \nEvent Host: Jonathan Castello\, Ph.D. Student\, Computer Science and Engineering \nAdvisor: Lindsey Kuper  \nZoom- https://ucsc.zoom.us/j/98171466380?pwd=L2rkpr8tEt0MZamYbxxPTfvhAd4gl6.1 \nPasscode- 990848 \n 
URL:https://events.ucsc.edu/event/castello-j-cse-space-mission-simulation-from-the-outside-in/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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END:VEVENT
END:VCALENDAR